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论文编号：	14670
作者编号：	2120223627
上传时间：	2024/6/5 20:25:14
中文题目：	考虑患者偏好的护理中心服务预约与调度的集成机制研究
英文题目：	An Integrated Mechanism for Patient-Centered Service Appointment and Scheduling Considering Patient Preferencess
指导老师：	梁峰
中文关键字：	家庭护理服务;预约调度;马尔科夫决策;累积前景理论;带时间窗的车辆路径问题
英文关键字：	Home Nursing Services; Appointment Scheduling; Markov Decision; Cumulative Prospect Theory; Vehicle Routing Problem with Time Windows
中文摘要：	全球人口老龄化进程加快，我国人口老龄化现象也越来越严重，随之产生的医疗和护理需求也越来越多，但我国医疗资源短缺，医护服务发展起步较晚，因此老年人的医疗护理需求正成为民生管理相关的关键议题。在缓解医疗资源紧缺和提升医疗护理效率方面，家庭护理服务因具有缩短服务时间、缓解医疗资源占用等优势，而成为解决上述问题的关键办法。我国的家庭护理服务尚处于起步阶段，覆盖城市不广。现有研究主要集中在宏观政策层面，对于家庭护理服务的运营管理机制研究不足。其中针对运营管理问题进行研究的文章多关注于已知客户需求的护理人员路线规划，未考虑患者偏好和护理人员资质对预约调度的影响。 因此，本研究提出建立一个考虑患者对护理时间和服务人员偏好的家庭护理服务预约与调度集成系统，该集成系统分为预约阶段和服务阶段。在预约阶段，基于患者的护理需求类别，利用马尔可夫决策过程模型建立护理中心预约决策系统，系统将以护理中心期望收益最大为前提，决定是否接受该患者的预约请求; 在服务执行阶段，考虑患者对服务时间和人员的偏好，采用累积前景理论衡量患者满意度，构建了一个目标为最大化患者满意度和最小化护理中心运营成本的带时间窗的路线规划模型，从而为护理师分配待服务患者和其调度路径，并输出最终的调度方案。 最后，运用 A*算法与遗传算法求解护理中心服务调度模型，同时根据实践经验模拟仿真算例，以验证算法和模型的有效性。结合相关参数的灵敏度分析结果，得出了考虑患者偏好的护理中心服务预约与调度的集成机制研究结论，并进一步结合实践总结护理中心运营管理启示，归纳本文的研究不足和未来的研究展望。
英文摘要：	In light of the global trend towards an aging population, the medical treatment resources, nursing resources and endowment resources are in short supply in our country, the medical and health care of the elderly is an important management problem in the field of people's livelihood. Home nursing services characterized by their unique potential to alleviate medical resource shortages and optimize healthcare resource utilization. The development of home nursing services within our nation is embryonic, the service is available in only a few cities, and hampered by a paucity of skilled personnel. Predominant research in this domain has skewed towards macro- management, focusing on policy analysis while operational management mechanisms remain underexplored. Furthermore, existing studies predominantly address the problem of path planning for nursing staff without incorporating patient preferences or nurse qualifications into the scheduling model. Given that the majority of nursing service beneficiaries are patients with chronic conditions, integrating service requests into the scheduling model could markedly enhance the congruence between patient needs and nursing service. This integration promises to reduce operational expenditures for nursing centers and elevate patient satisfaction. This study introduces a novel pre-scheduling system for home nursing services, which systematically incorporates patient preferences regarding service timing and personnel selection. The proposed system unfolds in two sequential phases. Initially, the pre-scheduling phase employs a Markov decision process model to categorize and prioritize nursing service demands, the model will then decide whether to accept the patient's demand for services. Subsequent to this phase, and prior to the initiation of services, the study designs a path planning model with specific time windows and the patient's choice of nursing staff. This model endeavors to maximize patient satisfaction while concurrently minimizing the operational costs for nursing centers by optimizing the daily routing of nursing personnel. Employing dynamic programming's value iteration strategy alongside an enhanced genetic algorithm, this dissertation rigorously simulates numerical examples for each phase, thereby validating the efficacy of the proposed model and algorithm design in optimizing home nursing service appointment scheduling. Insights gleaned from these simulations, coupled with a sensitivity analysis, offer profound implications for the strategic management of home nursing services. The dissertation concludes by delineating the limitations inherent in the current study and predicting directions for future research.
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